NDLI: Wind Turbine Accidents: A Data Mining Study

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Wind Turbine Accidents: A Data Mining Study

Content Provider	Scilit
Author	Ertek, Gurdal Pakter, Sena Ulun, Soner
Copyright Year	2018
Description	Journal: Ssrn Electronic Journal While the global production of wind energy is increasing, there exists a significant gap in the academic and practice literature regarding the analysis of wind turbine accidents. Our paper presents the results obtained from the analysis of 240 wind turbine accidents from around the world. The main focus of our paper is revealing the associations between several factors and deaths & injuries in wind turbine accidents. Specifically, the associations of death and injuries with the stage of the wind turbine’s life cycle (transportation, construction, operation, and maintenance) and the main cause factor categories (human, system/equipment, and nature) were investigated. To this end, we conducted a detailed investigation that integrates exploratory and statistical data analysis methods with data mining methods. The paper presents a multitude of insights regarding the accidents and discusses implications for wind turbine manufacturers, engineering and insurance companies, and government organizations.
Related Links	http://research.sabanciuniv.edu/36683/1/asian_et_al_2017_Wind_Turbine_Accidents.pdf https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=3148853
ISSN	10914358
e-ISSN	15565068
DOI	10.2139/ssrn.3148853
Journal	Ssrn Electronic Journal
Language	English
Publisher	Elsevier BV
Publisher Date	2018-03-25
Access Restriction	Open
Subject Keyword	Journal: Ssrn Electronic Journal Transportation Science and Technology Turbine Accidents Wind Turbine Data Mining Methods Data Analysis Methods
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Psychiatry and Mental Health

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